Investigator

Benjamin Pickwell-Smith

University of Leeds

About

BPBenjamin Pickwell…
Papers(3)
Where are the inequal…Risk of secondary mye…Are there inequalitie…
Collaborators(10)
David DodwellIreneous SoyiriKenneth K C ManLewis W. PatonLi WeiLuke SteventonMichael LindPinkie ChambersShibani NicumZhe Wang
Institutions(6)
Hull York Medical Sch…University of OxfordAintree University Ho…Unknown InstitutionUniversity College Lo…Second Hospital of Sh…

Papers

Where are the inequalities in ovarian cancer care in a country with universal healthcare? A systematic review and narrative synthesis

Patients diagnosed with ovarian cancer from more deprived areas may face barriers to accessing timely, quality healthcare. We evaluated the literature for any association between socioeconomic group, treatments received and hospital delay among patients diagnosed with ovarian cancer in the United Kingdom, a country with universal healthcare. We searched MEDLINE, EMBASE, CINAHL, CENTRAL, SCIE, AMED, PsycINFO and HMIC from inception to January 2023. Forward and backward citation searches were conducted. Two reviewers independently reviewed titles, abstracts, and full-text articles. UK-based studies were included if they reported socioeconomic measures and an association with either treatments received or hospital delay. The inclusion of studies from one country ensured greater comparability. Risk of bias was assessed using the QUIPS tool, and a narrative synthesis was conducted. The review is reported to PRISMA 2020 and registered with PROSPERO [CRD42022332071]. Out of 2876 references screened, ten were included. Eight studies evaluated treatments received, and two evaluated hospital delays. We consistently observed socioeconomic inequalities in the likelihood of surgery (range of odds ratios 0.24-0.99) and chemotherapy (range of odds ratios 0.70-0.99) among patients from the most, compared with the least, deprived areas. There were no associations between socioeconomic groups and hospital delay. Ovarian cancer treatments differed between socioeconomic groups despite the availability of universal healthcare. Further research is needed to understand why, though suggested reasons include patient choice, health literacy, and financial and employment factors. Qualitative research would provide a rich understanding of the complex factors that drive these inequalities.

Risk of secondary myelodysplastic syndromes and acute myeloid leukaemia following poly(ADP-ribose) polymerase inhibitor treatment for advanced-stage recurrent ovarian cancer: A retrospective cohort study in England

Poly(ADP-ribose) polymerase inhibitors (PARPi) maintenance therapies are used to treat advanced ovarian cancer in first line and recurrent settings. Because of concerns about associations between PARPi therapy and secondary cancers myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML), a meta-analysis of clinical trials was conducted, reporting MDS/AML incidence of 0.73 %; however, clinical trial populations are highly selective and may not reflect incidence in the wider population. This retrospective cohort study calculated incidence of MDS/AML within five years of completing first-line chemotherapy + /- PARPi maintenance for recurrent, advanced-stage ovarian cancer. Absolute and relative risks were calculated and compared to meta-analysis. Of 11,531 included patients, 1529 received PARPi and 10,002 chemotherapy only. Absolute risk of MDS/AML was 0.3 % (n = 5/1529) for chemotherapy + PARPi maintenance therapy versus 0.1 % (n = 10/10,002) for chemotherapy alone. Relative risk was 2.97 (95 % CI 1.02, 8.68, p = 0.046) in patients receiving PARPi maintenance versus chemotherapy alone. Relative risk of MDS/AML was greater in patients treated with PARPi; however, absolute risk was low in both treatment groups and lower than in the meta-analysis of trials. This analysis suggests small increased relative risk of MDS/AML associated with PARPi maintenance versus chemotherapy only, but not increased absolute risk.

Are there inequalities in ovarian cancer diagnosis and treatment in England? A population-based study.

Ovarian cancer ranks as the sixth leading cause of cancer-related mortality among women. Notably, there is a deprivation gradient in survival rates, with individuals from more affluent socioeconomic groups more likely to be alive at five years following diagnosis. This study examines disparities in treatment received and the timeliness of diagnosis and treatment across different socioeconomic groups in England, a country with universal healthcare. The Cancer Registry identified a retrospective cohort of patients diagnosed with ovarian cancer in England between 2016 and 2017. Registry data were linked to Hospital Episode Statistics, Cancer Pathway, Systematic Anti-Cancer Dataset, and Diagnostic Imaging Datasets. The odds of surgery and chemotherapy were evaluated using logistic regression. The secondary care diagnostic interval methodology was used to calculate the starting point for the measurement of time to diagnosis and treatment and was analysed using quantile regression. All analyses were conducted using Stata v17. The study was registered on ClinicalTrials.gov (NCT05185388). A total of 9572 patients were included in the analysis. Area deprivation was a significant predictor of receipt of surgery and chemotherapy. The odds of having surgery and chemotherapy were 0.68 (95 % CI 0.57-0.82) and 0.68 (95 % CI 0.56-0.81), respectively, for patients from the most deprived quintile, adjusting for other factors. The interval measured from the beginning of the diagnostic pathway to treatment was significantly longer for patients from the most, compared with the least deprived areas after adjusting for important factors (median difference 4.50 days [95 % CI 2.72-6.28]). In this large cohort of patients with ovarian cancer in England, we demonstrated that patients from more deprived areas are less likely to receive surgery or chemotherapy and wait longer to commence treatment. Further research is needed to understand why and what evidence-based actions can reduce these inequalities in treatment and timeliness.

33Works
3Papers
11Collaborators

Positions

Researcher

University of Leeds

2024–

NIHR Clinical Lecturer

University of Leeds · Leeds Institute of Medical Research (LIMR)

2024–

Clinical Academic Research Fellow in Medical Oncology

Leeds Teaching Hospitals NHS Trust

2023–

Specialist Registrar in Medical Oncology

Leeds Teaching Hospitals NHS Trust

2020–

Clinical Research Fellow

Hull York Medical School · Academy of Primary Care

Education

2023

PhD

Hull York Medical School

2013

MBChB

Keele University · School of Medicine

Country

GB

Keywords
InequalitiesRoutinely collected dataDelays to diagnosisRural and coastalHealth policyCommon data models
Links & IDs
0009-0003-1941-6444

Scopus: 56586169300